docs

docs/src/example.md

@@ -245,5 +245,16 @@ Visually, it is almost immediately understood that there are no worthy differenc
 Given that the age group plays a significant role in the study, we will now estimate the sample size by yearly intervals in order to better compare the age groups.
 
 ```@example 2
-ess = nessie(@formula(Surv(time,status)~age65), colrec, slopop)
-```
+elt, ess = nessie(@formula(Surv(time,status)~age65), colrec, slopop)
+elt
+```
+
+The expected life time for the younger patients is significatively higher than for older patients (24.78 years > 10.29 years).
+
+```@example 2
+hcat(ess[:,3]...)
+```
+
+Finally, the table above represents yearly expected sample sizes for both age groups under 65 and above, with the second column representing the latter. We can see that the sample size decreases for the older patients in a much more dramatic way than for the younger ages.
+
+Unsurprisingly, we can thus conclude that age plays an important role in the study.

docs/src/getting_started.md

@@ -123,10 +123,14 @@ This function is highly dependant on the `Life` function taken from the `RateTab
 
 The sample size is thus taken by the following formula:
 
-$$ ESS = \sum_i^N S_{P_i} * exp(-\Lambda_p) $$
+$$ESS(t) = \sum_i^N S_{P_i}(t) * \exp(-\Lambda_{P_i}(t))$$
 
 While the estimated lifepsan is directly taken from the `expectation` function. 
 
+```@docs
+nessie
+```
+
 ## References
 
 ```@bibliography

src/Nessie.jl

@@ -18,9 +18,11 @@ struct Nessie
 end
 
 """
-    nessie(formula, data, ratetable)
+    nessie 
 
-The Nessie function estimates the sample size by yearly intervals as well as averages an estimated lifespan left for a given group.  
+To call this function, use the formula below: 
+
+    nessie(@formula(Surv(time,status)~covariate), data, ratetable)
 """
 function nessie(args...)
     r = fit(Nessie,args...)